literature-review

$29

Visual Enhancement with Scientific Schematics

⚠️ MANDATORY: Every literature review MUST include at least 1-2 AI-generated figures using the scientific-schematics skill.

This is not optional. Literature reviews without visual elements are incomplete. Before finalizing any document:

• Generate at minimum ONE schematic or diagram (e.g., PRISMA flow diagram for systematic reviews)

• Prefer 2-3 figures for comprehensive reviews (search strategy flowchart, thematic synthesis diagram, conceptual framework)

How to generate figures:

• Use the scientific-schematics skill to generate AI-powered publication-quality diagrams

• Simply describe your desired diagram in natural language

• Nano Banana Pro will automatically generate, review, and refine the schematic

How to generate schematics:

python scripts/generate_schematic.py "your diagram description" -o figures/output.png

The AI will automatically:

• Create publication-quality images with proper formatting

• Review and refine through multiple iterations

• Ensure accessibility (colorblind-friendly, high contrast)

• Save outputs in the figures/ directory

When to add schematics:

• PRISMA flow diagrams for systematic reviews

• Literature search strategy flowcharts

• Thematic synthesis diagrams

• Research gap visualization maps

• Citation network diagrams

• Conceptual framework illustrations

• Any complex concept that benefits from visualization

For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.

Core Workflow

Literature reviews follow a structured, multi-phase workflow:

Phase 1: Planning and Scoping

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Define Research Question: Use PICO framework (Population, Intervention, Comparison, Outcome) for clinical/biomedical reviews

• Example: "What is the efficacy of CRISPR-Cas9 (I) for treating sickle cell disease (P) compared to standard care (C)?"

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Establish Scope and Objectives:

• Define clear, specific research questions

• Determine review type (narrative, systematic, scoping, meta-analysis)

• Set boundaries (time period, geographic scope, study types)

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Develop Search Strategy:

• Identify 2-4 main concepts from research question

• List synonyms, abbreviations, and related terms for each concept

• Plan Boolean operators (AND, OR, NOT) to combine terms

• Select minimum 3 complementary databases

• **Use the parallel-web skill (parallel-cli search) for initial scoping** to quickly gauge the landscape before formal database searches

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Set Inclusion/Exclusion Criteria:

• Date range (e.g., last 10 years: 2015-2024)

• Language (typically English, or specify multilingual)

• Publication types (peer-reviewed, preprints, reviews)

• Study designs (RCTs, observational, in vitro, etc.)

• Document all criteria clearly

Phase 2: Systematic Literature Search

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Multi-Database Search:

Select databases appropriate for the domain. Always start with parallel-web for broad academic coverage, then supplement with domain-specific databases.

Web-Based Academic Search (parallel-web skill — START HERE):

• Use parallel-cli search with academic domain filtering for broad scholarly coverage

• Run two searches: academic-focused + general to catch all relevant sources

# Academic-focused search across scholarly sources

parallel-cli search "your research topic" -q "keyword1" -q "keyword2" \

  --json --max-results 10 --excerpt-max-chars-total 27000 \

  --include-domains "scholar.google.com,arxiv.org,pubmed.ncbi.nlm.nih.gov,semanticscholar.org,biorxiv.org,medrxiv.org,ncbi.nlm.nih.gov,nature.com,science.org,ieee.org,acm.org,springer.com,wiley.com,cell.com,pnas.org,nih.gov" \

  -o sources/litreview_<topic>-academic.json

# General search for supplementary sources

parallel-cli search "your research topic" -q "keyword1" -q "keyword2" \

  --json --max-results 10 --excerpt-max-chars-total 27000 \

  -o sources/litreview_<topic>-general.json

• Use parallel-cli extract to fetch full content from specific paper URLs or PDFs found in search results

parallel-cli extract "https://arxiv.org/abs/XXXX.XXXXX" --json

Biomedical & Life Sciences:

• Use gget skill: gget search pubmed "search terms" for PubMed/PMC

• Use gget skill: gget search biorxiv "search terms" for preprints

• Use bioservices skill for ChEMBL, KEGG, UniProt, etc.

General Scientific Literature:

• Search arXiv via direct API (preprints in physics, math, CS, q-bio)

• Search Semantic Scholar via API (200M+ papers, cross-disciplinary)

• Use Google Scholar for comprehensive coverage (manual or careful scraping)

Specialized Databases:

• Use gget alphafold for protein structures

• Use gget cosmic for cancer genomics

• Use datacommons-client for demographic/statistical data

• Use specialized databases as appropriate for the domain

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Document Search Parameters:

## Search Strategy

### Database: PubMed

- **Date searched**: 2024-10-25

- **Date range**: 2015-01-01 to 2024-10-25

- **Search string**:

("CRISPR"[Title] OR "Cas9"[Title])

AND ("sickle cell"[MeSH] OR "SCD"[Title/Abstract])

AND 2015:2024[Publication Date]

- **Results**: 247 articles

Repeat for each database searched.

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Export and Aggregate Results:

• Export results in JSON format from each database

• Combine all results into a single file

• Use scripts/search_databases.py for post-processing:

python search_databases.py combined_results.json \

  --deduplicate \

  --format markdown \

  --output aggregated_results.md

Phase 3: Screening and Selection

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Deduplication:

python search_databases.py results.json --deduplicate --output unique_results.json

• Removes duplicates by DOI (primary) or title (fallback)

• Document number of duplicates removed

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Title Screening:

• Review all titles against inclusion/exclusion criteria

• Exclude obviously irrelevant studies

• Document number excluded at this stage

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Abstract Screening:

• Read abstracts of remaining studies

• Apply inclusion/exclusion criteria rigorously

• Document reasons for exclusion

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Full-Text Screening:

• Obtain full texts of remaining studies

• Conduct detailed review against all criteria

• Document specific reasons for exclusion

• Record final number of included studies

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Create PRISMA Flow Diagram:

Initial search: n = X

├─ After deduplication: n = Y

├─ After title screening: n = Z

├─ After abstract screening: n = A

└─ Included in review: n = B

Phase 4: Data Extraction and Quality Assessment

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Extract Key Data from each included study:

• Study metadata (authors, year, journal, DOI)

• Study design and methods

• Sample size and population characteristics

• Key findings and results

• Limitations noted by authors

• Funding sources and conflicts of interest

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Assess Study Quality:

• For RCTs: Use Cochrane Risk of Bias tool

• For observational studies: Use Newcastle-Ottawa Scale

• For systematic reviews: Use AMSTAR 2

• Rate each study: High, Moderate, Low, or Very Low quality

• Consider excluding very low-quality studies

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Organize by Themes:

• Identify 3-5 major themes across studies

• Group studies by theme (studies may appear in multiple themes)

• Note patterns, consensus, and controversies

Phase 5: Synthesis and Analysis

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Create Review Document from template:

cp assets/review_template.md my_literature_review.md

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Write Thematic Synthesis (NOT study-by-study summaries):

• Organize Results section by themes or research questions

• Synthesize findings across multiple studies within each theme

• Compare and contrast different approaches and results

• Identify consensus areas and points of controversy

• Highlight the strongest evidence

Example structure:

#### 3.3.1 Theme: CRISPR Delivery Methods

Multiple delivery approaches have been investigated for therapeutic

gene editing. Viral vectors (AAV) were used in 15 studies^1-15^ and

showed high transduction efficiency (65-85%) but raised immunogenicity

concerns^3,7,12^. In contrast, lipid nanoparticles demonstrated lower

efficiency (40-60%) but improved safety profiles^16-23^.

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Critical Analysis:

• Evaluate methodological strengths and limitations across studies

• Assess quality and consistency of evidence

• Identify knowledge gaps and methodological gaps

• Note areas requiring future research

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Write Discussion:

• Interpret findings in broader context

• Discuss clinical, practical, or research implications

• Acknowledge limitations of the review itself

• Compare with previous reviews if applicable

• Propose specific future research directions

Phase 6: Citation Verification

CRITICAL: All citations must be verified for accuracy before final submission.

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Verify All DOIs:

python scripts/verify_citations.py my_literature_review.md

This script:

• Extracts all DOIs from the document

• Verifies each DOI resolves correctly

• Retrieves metadata from CrossRef

• Generates verification report

• Outputs properly formatted citations

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Review Verification Report:

• Check for any failed DOIs

• Verify author names, titles, and publication details match

• Correct any errors in the original document

• Re-run verification until all citations pass

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Format Citations Consistently:

• Choose one citation style and use throughout (see references/citation_styles.md)

• Common styles: APA, Nature, Vancouver, Chicago, IEEE

• Use verification script output to format citations correctly

• Ensure in-text citations match reference list format

Phase 7: Document Generation

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Generate PDF:

python scripts/generate_pdf.py my_literature_review.md \

  --citation-style apa \

  --output my_review.pdf

Options:

• --citation-style: apa, nature, chicago, vancouver, ieee

• --no-toc: Disable table of contents

• --no-numbers: Disable section numbering

• --check-deps: Check if pandoc/xelatex are installed

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Review Final Output:

• Check PDF formatting and layout

• Verify all sections are present

• Ensure citations render correctly

• Check that figures/tables appear properly

• Verify table of contents is accurate

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Quality Checklist:

• All DOIs verified with verify_citations.py

• Citations formatted consistently

• PRISMA flow diagram included (for systematic reviews)

• Search methodology fully documented

• Inclusion/exclusion criteria clearly stated

• Results organized thematically (not study-by-study)

• Quality assessment completed

• Limitations acknowledged

• References complete and accurate

• PDF generates without errors

Database-Specific Search Guidance

PubMed / PubMed Central

Access via gget skill:

# Search PubMed

gget search pubmed "CRISPR gene editing" -l 100

# Search with filters

# Use PubMed Advanced Search Builder to construct complex queries

# Then execute via gget or direct Entrez API

Search tips:

• Use MeSH terms: "sickle cell disease"[MeSH]

• Field tags: [Title], [Title/Abstract], [Author]

• Date filters: 2020:2024[Publication Date]

• Boolean operators: AND, OR, NOT

• See MeSH browser: https://meshb.nlm.nih.gov/search

bioRxiv / medRxiv

Access via gget skill:

gget search biorxiv "CRISPR sickle cell" -l 50

Important considerations:

• Preprints are not peer-reviewed

• Verify findings with caution

• Check if preprint has been published (CrossRef)

• Note preprint version and date

arXiv

Access via direct API or WebFetch:

# Example search categories:

# q-bio.QM (Quantitative Methods)

# q-bio.GN (Genomics)

# q-bio.MN (Molecular Networks)

# cs.LG (Machine Learning)

# stat.ML (Machine Learning Statistics)

# Search format: category AND terms

search_query = "cat:q-bio.QM AND ti:\"single cell sequencing\""

Semantic Scholar

Access via direct API (requires API key, or use free tier):

• 200M+ papers across all fields

• Excellent for cross-disciplinary searches

• Provides citation graphs and paper recommendations

• Use for finding highly influential papers

Specialized Biomedical Databases

Use appropriate skills:

• ChEMBL: bioservices skill for chemical bioactivity

• UniProt: gget or bioservices skill for protein information

• KEGG: bioservices skill for pathways and genes

• COSMIC: gget skill for cancer mutations

• AlphaFold: gget alphafold for protein structures

• PDB: gget or direct API for experimental structures

Citation Chaining

Expand search via citation networks:

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Forward citations (papers citing key papers):

• Use parallel-cli search to find papers citing a specific work:

parallel-cli search "papers citing [Author et al. Year] [paper title]" \

  -q "citing" -q "[key author]" \

  --json --max-results 10 --excerpt-max-chars-total 27000 \

  --include-domains "scholar.google.com,semanticscholar.org,arxiv.org,pubmed.ncbi.nlm.nih.gov" \

  -o sources/litreview_forward_citations.json

• Use Google Scholar "Cited by"

• Use Semantic Scholar or OpenAlex APIs

• Identifies newer research building on seminal work

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Backward citations (references from key papers):

• Use parallel-cli extract to fetch full text of key papers and extract their reference lists:

parallel-cli extract "https://doi.org/10.xxxx/yyyy" --json

• Extract references from included papers

• Identify highly cited foundational work

• Find papers cited by multiple included studies

Citation Style Guide

Detailed formatting guidelines are in references/citation_styles.md. Quick reference:

APA (7th Edition)

• In-text: (Smith et al., 2023)

• Reference: Smith, J. D., Johnson, M. L., & Williams, K. R. (2023). Title. Journal, 22(4), 301-318. https://doi.org/10.xxx/yyy

Nature

• In-text: Superscript numbers^1,2^

• Reference: Smith, J. D., Johnson, M. L. & Williams, K. R. Title. Nat. Rev. Drug Discov. 22, 301-318 (2023).

Vancouver

• In-text: Superscript numbers^1,2^

• Reference: Smith JD, Johnson ML, Williams KR. Title. Nat Rev Drug Discov. 2023;22(4):301-18.

Always verify citations with verify_citations.py before finalizing.

Prioritizing High-Impact Papers (CRITICAL)

Always prioritize influential, highly-cited papers from reputable authors and top venues. Quality matters more than quantity in literature reviews.

#### Citation Count Thresholds

Use citation counts to identify the most impactful papers:

Paper Age

Citation Threshold

Classification

0-3 years

20+ citations

Noteworthy

0-3 years

100+ citations

Highly Influential

3-7 years

100+ citations

Significant

3-7 years

500+ citations

Landmark Paper

7+ years

500+ citations

Seminal Work

7+ years

1000+ citations

Foundational

#### Journal and Venue Tiers

Prioritize papers from higher-tier venues:

• Tier 1 (Always Prefer): Nature, Science, Cell, NEJM, Lancet, JAMA, PNAS, Nature Medicine, Nature Biotechnology

• Tier 2 (Strong Preference): High-impact specialized journals (IF>10), top conferences (NeurIPS, ICML for ML/AI)

• Tier 3 (Include When Relevant): Respected specialized journals (IF 5-10)

• Tier 4 (Use Sparingly): Lower-impact peer-reviewed venues

#### Author Reputation Assessment

Prefer papers from:

• Senior researchers with high h-index (>40 in established fields)

• Leading research groups at recognized institutions (Harvard, Stanford, MIT, Oxford, etc.)

• Authors with multiple Tier-1 publications in the relevant field

• Researchers with recognized expertise (awards, editorial positions, society fellows)

#### Identifying Seminal Papers

For any topic, identify foundational work by:

• High citation count (typically 500+ for papers 5+ years old)

• Frequently cited by other included studies (appears in many reference lists)

• Published in Tier-1 venues (Nature, Science, Cell family)

• Written by field pioneers (often cited as establishing concepts)

Best Practices

Search Strategy

• Start with parallel-web: Use parallel-cli search with academic domains for initial broad coverage before querying specialized databases

• Use multiple databases (minimum 3): Ensures comprehensive coverage — parallel-web counts as one source

• Include preprint servers: Captures latest unpublished findings

• Document everything: Search strings, dates, result counts for reproducibility — save all parallel-cli output to sources/

• Test and refine: Run pilot searches, review results, adjust search terms

• Sort by citations: When available, sort search results by citation count to surface influential work first

• Use parallel-cli extract: Fetch full content from promising URLs found during search to verify relevance before full-text screening

Screening and Selection

• Use multiple databases (minimum 3): Ensures comprehensive coverage

• Include preprint servers: Captures latest unpublished findings

• Document everything: Search strings, dates, result counts for reproducibility

• Test and refine: Run pilot searches, review results, adjust search terms

Screening and Selection

• Use clear criteria: Document inclusion/exclusion criteria before screening

• Screen systematically: Title → Abstract → Full text

• Document exclusions: Record reasons for excluding studies

• Consider dual screening: For systematic reviews, have two reviewers screen independently

Synthesis

• Organize thematically: Group by themes, NOT by individual studies

• Synthesize across studies: Compare, contrast, identify patterns

• Be critical: Evaluate quality and consistency of evidence

• Identify gaps: Note what's missing or understudied

Quality and Reproducibility

• Assess study quality: Use appropriate quality assessment tools

• Verify all citations: Run verify_citations.py script

• Document methodology: Provide enough detail for others to reproduce

• Follow guidelines: Use PRISMA for systematic reviews

Writing

• Be objective: Present evidence fairly, acknowledge limitations

• Be systematic: Follow structured template

• Be specific: Include numbers, statistics, effect sizes where available

• Be clear: Use clear headings, logical flow, thematic organization

Common Pitfalls to Avoid

• Single database search: Misses relevant papers; always search multiple databases

• No search documentation: Makes review irreproducible; document all searches

• Study-by-study summary: Lacks synthesis; organize thematically instead

• Unverified citations: Leads to errors; always run verify_citations.py

• Too broad search: Yields thousands of irrelevant results; refine with specific terms

• Too narrow search: Misses relevant papers; include synonyms and related terms

• Ignoring preprints: Misses latest findings; include bioRxiv, medRxiv, arXiv

• No quality assessment: Treats all evidence equally; assess and report quality

• Publication bias: Only positive results published; note potential bias

• Outdated search: Field evolves rapidly; clearly state search date

Example Workflow

Complete workflow for a biomedical literature review:

# 1. Create review document from template

cp assets/review_template.md crispr_sickle_cell_review.md

# 2. Start with parallel-web for broad academic search

parallel-cli search "CRISPR Cas9 sickle cell disease gene therapy efficacy" \

  -q "CRISPR" -q "sickle cell" -q "gene therapy" \

  --json --max-results 10 --excerpt-max-chars-total 27000 \

  --include-domains "scholar.google.com,arxiv.org,pubmed.ncbi.nlm.nih.gov,semanticscholar.org,biorxiv.org,nature.com,science.org,cell.com,pnas.org,nih.gov" \

  -o sources/litreview_crispr_scd-academic.json

parallel-cli search "CRISPR sickle cell disease clinical trials treatment" \

  -q "CRISPR" -q "sickle cell" \

  --json --max-results 10 --excerpt-max-chars-total 27000 \

  -o sources/litreview_crispr_scd-general.json

# 3. Search specialized databases using appropriate skills

# - Use gget skill for PubMed, bioRxiv

# - Use direct API access for arXiv, Semantic Scholar

# - Export results in JSON format

# 4. Aggregate and process results (combine parallel-cli + database results)

python scripts/search_databases.py combined_results.json \

  --deduplicate \

  --rank citations \

  --year-start 2015 \

  --year-end 2024 \

  --format markdown \

  --output search_results.md \

  --summary

# 5. Screen results and extract data

# - Use parallel-cli extract to fetch full content from promising URLs

# - Manually screen titles, abstracts, full texts

# - Extract key data into the review document

# - Organize by themes

# 6. Write the review following template structure

# - Introduction with clear objectives

# - Detailed methodology section

# - Results organized thematically

# - Critical discussion

# - Clear conclusions

# 7. Verify all citations

python scripts/verify_citations.py crispr_sickle_cell_review.md

# Review the citation report

cat crispr_sickle_cell_review_citation_report.json

# Fix any failed citations and re-verify

python scripts/verify_citations.py crispr_sickle_cell_review.md

# 8. Generate professional PDF

python scripts/generate_pdf.py crispr_sickle_cell_review.md \

  --citation-style nature \

  --output crispr_sickle_cell_review.pdf

# 9. Review final PDF and markdown outputs

Integration with Other Skills

This skill works seamlessly with other scientific skills:

Web Search & Extraction (parallel-web skill — PRIMARY)

• parallel-cli search: Broad academic and general web search with domain filtering — use for initial scoping, finding papers, citation chaining, and supplementary searches

• parallel-cli extract: Fetch full content from paper URLs, journal websites, and preprint servers — use for reading abstracts, extracting reference lists, and verifying paper details

• parallel-cli search --include-domains: Academic-focused search across scholarly domains (arxiv.org, pubmed, nature.com, etc.)

Database Access Skills

• gget: PubMed, bioRxiv, COSMIC, AlphaFold, Ensembl, UniProt

• bioservices: ChEMBL, KEGG, Reactome, UniProt, PubChem

• datacommons-client: Demographics, economics, health statistics

Analysis Skills

• pydeseq2: RNA-seq differential expression (for methods sections)

• scanpy: Single-cell analysis (for methods sections)

• anndata: Single-cell data (for methods sections)

• biopython: Sequence analysis (for background sections)

Visualization Skills

• matplotlib: Generate figures and plots for review

• seaborn: Statistical visualizations

Writing Skills

• brand-guidelines: Apply institutional branding to PDF

• internal-comms: Adapt review for different audiences

Resources

Bundled Resources

Scripts:

• scripts/verify_citations.py: Verify DOIs and generate formatted citations

• scripts/generate_pdf.py: Convert markdown to professional PDF

• scripts/search_databases.py: Process, deduplicate, and format search results

References:

• references/citation_styles.md: Detailed citation formatting guide (APA, Nature, Vancouver, Chicago, IEEE)

• references/database_strategies.md: Comprehensive database search strategies

Assets:

• assets/review_template.md: Complete literature review template with all sections

External Resources

Guidelines:

• PRISMA (Systematic Reviews): http://www.prisma-statement.org/

• Cochrane Handbook: https://training.cochrane.org/handbook

• AMSTAR 2 (Review Quality): https://amstar.ca/

Tools:

• MeSH Browser: https://meshb.nlm.nih.gov/search

• PubMed Advanced Search: https://pubmed.ncbi.nlm.nih.gov/advanced/

• Boolean Search Guide: https://www.ncbi.nlm.nih.gov/books/NBK3827/

Citation Styles:

• APA Style: https://apastyle.apa.org/

• Nature Portfolio: https://www.nature.com/nature-portfolio/editorial-policies/reporting-standards

• NLM/Vancouver: https://www.nlm.nih.gov/bsd/uniform_requirements.html

Dependencies

Required CLI Tools

# parallel-cli (PRIMARY — for web search and URL extraction)

curl -fsSL https://parallel.ai/install.sh | bash

# Or: uv tool install "parallel-web-tools[cli]"

# Authenticate: parallel-cli auth

Required Python Packages

pip install requests  # For citation verification

Required System Tools

# For PDF generation

brew install pandoc  # macOS

apt-get install pandoc  # Linux

# For LaTeX (PDF generation)

brew install --cask mactex  # macOS

apt-get install texlive-xetex  # Linux

Check dependencies:

python scripts/generate_pdf.py --check-deps

Summary

This literature-review skill provides:

• Systematic methodology following academic best practices

• Parallel-web powered search using parallel-cli search for fast, broad academic literature discovery with scholarly domain filtering

• Multi-database integration via existing scientific skills (gget, bioservices, datacommons-client)

• Citation verification ensuring accuracy and credibility

• Professional output in markdown and PDF formats

• Comprehensive guidance covering the entire review process

• Quality assurance with verification and validation tools

• Reproducibility through detailed documentation requirements

Conduct thorough, rigorous literature reviews that meet academic standards and provide comprehensive synthesis of current knowledge in any domain.